Intelligent reflecting surfaces enabled cognitive internet of things based on practical pathloss model

In this paper, we aim to unlock the potential of intelligent reflecting surfaces (IRSs) in cognitive internet of things (loT). Considering that the secondary IoT devices send messages to the secondary access point (SAP) by sharing the spectrum with the primary network, the interference is introduced by the IoT devices to the primary access point (PAP) which profits from the IoT devices by pricing the interference power charged by them. A practical path loss model is adopted such that the IRSs deployed between the IoT devices and SAP serve as diffuse scatterers, but each reflected signal can be aligned with its own desired direction. Moreover, two transmission policies of the secondary network are investigated without/with a successive interference cancellation (SIC) technique. The signal-to-interference plus noise ratio (SINR) balancing is considered to overcome the near- far effect of the IoT devices so as to allocate the resource fairly among them. We propose a Stackelberg game strategy to characterize the interaction between primary and secondary networks. For the proposed game, the Stackelberg equilibrium is analytically derived to optimally obtain the closed-form solution of the power allocation and interference pricing. Numerical results are demonstrated to validate the performance of the theoretical derivations.